






import pytest

import datasets


# Import fixture modules as plugins
UpperCAmelCase__      			=						['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']







def     a_   (__A				,       __A      )				->						Optional[Any]:



					"""simple docstring"""
					# Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
					for item in items:
										if any(marker in item.keywords for marker in ["integration", "unit"]      ):
															continue
										item.add_marker(pytest.mark.unit      )







def     a_   (__A      )				->						Union[str, Any]:



					"""simple docstring"""
					config.addinivalue_line("markers"				,       "torchaudio_latest: mark test to run with torchaudio>=0.12"      )







@pytest.fixture(autouse=_A      )
def     a_   (__A				,       __A      )				->						Dict:



					"""simple docstring"""
					# test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
					__a					:						Any      =					tmp_path_factory.getbasetemp() / 'cache'
					__a					:						Dict      =					test_hf_cache_home / 'datasets'
					__a					:						List[Any]      =					test_hf_cache_home / 'metrics'
					__a					:						Tuple      =					test_hf_cache_home / 'modules'
					monkeypatch.setattr("datasets.config.HF_DATASETS_CACHE"				,       str(_A      )      )
					monkeypatch.setattr("datasets.config.HF_METRICS_CACHE"				,       str(_A      )      )
					monkeypatch.setattr("datasets.config.HF_MODULES_CACHE"				,       str(_A      )      )
					__a					:						List[Any]      =					test_hf_datasets_cache / 'downloads'
					monkeypatch.setattr("datasets.config.DOWNLOADED_DATASETS_PATH"				,       str(_A      )      )
					__a					:						int      =					test_hf_datasets_cache / 'downloads' / 'extracted'
					monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_PATH"				,       str(_A      )      )







@pytest.fixture(autouse=_A				,       scope="session"      )
def     a_   ()				->						str:



					"""simple docstring"""
					datasets.disable_progress_bar()







@pytest.fixture(autouse=_A      )
def     a_   (__A      )				->						Tuple:



					"""simple docstring"""
					# don't take tests into account when counting downloads
					monkeypatch.setattr("datasets.config.HF_UPDATE_DOWNLOAD_COUNTS"				,       _A      )







@pytest.fixture
def     a_   (__A      )				->						List[str]:



					"""simple docstring"""
					# Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
					# To be removed once SQLAlchemy 2.0 supported
					monkeypatch.setattr("sqlalchemy.util.deprecations.SILENCE_UBER_WARNING"				,       _A      )










'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:   List[str]					=		logging.get_logger(__name__)

lowerCAmelCase:   Union[str, Any]					=		{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """lilt"""







    def __init__( self					:    str		,     __snake_case					:    Dict=3_05_22		,     __snake_case					:    int=7_68		,     __snake_case					:    Union[str, Any]=12		,     __snake_case					:    Optional[Any]=12		,     __snake_case					:    Dict=30_72		,     __snake_case					:    Tuple="gelu"		,     __snake_case					:    Dict=0.1		,     __snake_case					:    List[Any]=0.1		,     __snake_case					:    List[str]=5_12		,     __snake_case					:    List[str]=2		,     __snake_case					:    str=0.02		,     __snake_case					:    Dict=1e-1_2		,     __snake_case					:    int=0		,     __snake_case					:    Any="absolute"		,     __snake_case					:    Tuple=None		,     __snake_case					:    Tuple=4		,     __snake_case					:    List[str]=10_24		,     **__snake_case					:    Union[str, Any]		,     ):
      super().__init__(pad_token_id=__snake_case		,     **__snake_case      )

      a		:   str	  =	vocab_size
      a		:   Optional[Any]	  =	hidden_size
      a		:   Union[str, Any]	  =	num_hidden_layers
      a		:   Tuple	  =	num_attention_heads
      a		:   Optional[Any]	  =	hidden_act
      a		:   Union[str, Any]	  =	intermediate_size
      a		:   Optional[Any]	  =	hidden_dropout_prob
      a		:   Tuple	  =	attention_probs_dropout_prob
      a		:   str	  =	max_position_embeddings
      a		:   Any	  =	type_vocab_size
      a		:   Union[str, Any]	  =	initializer_range
      a		:   int	  =	layer_norm_eps
      a		:   Any	  =	position_embedding_type
      a		:   Any	  =	classifier_dropout
      a		:   str	  =	channel_shrink_ratio
      a		:   Optional[Any]	  =	max_ad_position_embeddings